Markov Switching Predictors Under Asymmetric Loss Functions

Francesco Giordano () and Marcella Niglio ()
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Francesco Giordano: University of Salerno
Marcella Niglio: University of Salerno

A chapter in Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2021, pp 251-256 from Springer

Abstract: Abstract There is empirical evidence that in economic and financial domains the forecast generation is often based on asymmetric losses that allow to differently treat positive and negative forecasts errors. It has led to the introduction of predictors that differently consider the cost related to the over and underprediction. It this context we focus the attention on the generation of forecasts from nonlinear Markov Switching models using the asymmetric LinEx loss function. After the presentation of the model, we introduce an asymmetric LinEx predictor for a well defined variant of Markov Switching structure, generalizing some results given in the literature and focusing the attention on the theoretical formulation of the predictor and on the properties mainly related to its bias. These results are illustrated in an example that gives evidence of some features of the new predictor.

Keywords: Markov switching; Asymmetric predictors; LinEx loss (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-78965-7_37

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DOI: 10.1007/978-3-030-78965-7_37

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